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Advanced Machine Learning application for Permeability Prediction for (M) Formation in an Iraqi Oil Field
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Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy and the performance of the algorithms. The random forest algorithm was the most accurate method leading to lowest Root Mean Square Prediction Error (RMSPE) and highest Adjusted R-Square than multiple linear regression algorithm for both training and testing subset respectively. Thus, random Forest algorithm is more trustable in permeability prediction in non-cored intervals and its distribution in the geological model.

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Keratoconus Severity Detection From Elevation, Topography and Pachymetry Raw Data Using a Machine Learning Approach
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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
User (K-Means) for clustering in Data Mining with application
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  The great scientific progress has led to widespread Information as information accumulates in large databases is important in trying to revise and compile this vast amount of data and, where its purpose to extract hidden information or classified data under their relations with each other in order to take advantage of them for technical purposes.

      And work with data mining (DM) is appropriate in this area because of the importance of research in the (K-Means) algorithm for clustering data in fact applied with effect can be observed in variables by changing the sample size (n) and the number of clusters (K)

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Publication Date
Wed Dec 27 2023
Journal Name
Journal Of Planner And Development
The dynamics of the oil industry in shaping land uses: a case study of the Zubair oil field
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The emergence of oil fields and subsequent changes in adjacent land use are known to affect settlements and communities. Everywhere the industry emerges, there is little understanding about the impact of oil fields on land use in the surrounding areas. The oil industry in Iraq is one of the most important industries and is almost the main industry in the Iraqi economic sector, and it is very clear that this industry is spread over large areas, and at the same time adjoins with population communities linked to it developmentally.

The rapid development and expansion of oil extraction activities in various regions has led to many challenges related to land-use planning and management. Here, the problem of research  arises on th

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Publication Date
Mon Feb 04 2019
Journal Name
Iraqi Journal Of Physics
Naturally occurring radioactive materials and related hazard indices in Ahdeb oil field
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In this work, measurements of activity concentration of naturally occurring radioactive materials (NORM) isotopes and their related hazard indices for several materials such as crude oil, sludge and water in Ahdeb oil fields in Waste governorate using high pure germanium coaxial detection technique. The average values for crude oil samples were174.72Bq/l, 43.46Bq/l, 355.07Bq/l, 264.21Bq/l, 122.52nGy/h, 0.7138, 1.1861, 0.601 mSv/y, 0.1503mSv/y and 1.8361 for Ra-226, Ac-228, K-40, Ra eq, D, H-external and H-internal respectively. According to the results; the ratio between 238U to 232Th was 4, which represents the natural ratio in the crust earth; therefore, one can be strongly suggested that the geo-stricture of the

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Publication Date
Thu Jan 30 2020
Journal Name
Journal Of Engineering
Calculation of Pressure Loss of Two Drilling Muds in Noor Oil Field
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In this work, calculation of pressure losses in circulating system for two drilling muds is evaluated in Noor oil field. Two types of drilling muds that were used for drilling section 12 1/4" and 8 3/4" which are Salt saturated mud and Ferro Chrome Lignosulfonate-Chrome Lignite mud. These calculations are based on field data that were gathered from the drilling site of well Noor-15, which are included, rheological data, flow data and specification of drill string. Based on the obtained results, the best rheological model that fit their data is the Herschel-Bulkley model according to correlation coefficient value for their two drilling mud. Also, the difference between the calculated pressure lo

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Publication Date
Sat Feb 01 2020
Journal Name
International Journal Of Computer Science And Mobile Computing
Hierarchical Fixed Prediction of Mixed based for Medical Image Compression.
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Publication Date
Tue Sep 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Creep-Fatigue Interaction Damage for Polyamide 6,6 Composites
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    This paper aims to study the damage generated due to creep-fatigue interaction behaviors in solid polyamide 6,6 and its composites that include 1%wt of carbon nanotubes or 30% wt short carbon fiber prepared by an injection technique. The investigation also includes studying the influence of applied temperatures higher than the glass transition temperatures on mechanical properties. The obtained results showed that the addition of reinforcement materials increased all the mechanical properties, while the increase in test temperature reduced all mechanical properties, especially for polyamide 6,6. The creep-fatigue interaction resistance also improved due to the addition of reinforcement materials by inc

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Publication Date
Tue Aug 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Prediction of Biodegradability Possibility for Sewage of the Dairy Industry
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he dairy industry is one of the industrial activities classified within the food industries in all phases of the dairy industry, which leads to an increase in the amount of wastewater discharged from this industry. The study was conducted in the Abu Ghraib dairy factory, classified as one of the central factories in Iraq, located in the west of Baghdad governorate, with a design capacity of 22,815 tons of dairy products. The characteristics of the liquid waste generated from the factory were determined for the following parameters biological oxygen demand (BOD5), Chemical oxygen demand (COD), total suspended solids (TSS), pH, nitrate, phosphate, chloride, and sulfate with an average value of (1079, 1945, 323, 9.2, 24, 2

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Publication Date
Mon Dec 24 2018
Journal Name
Civil Engineering Journal
Artificial Neural Network Model for the Prediction of Groundwater Quality
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The present article delves into the examination of groundwater quality, based on WQI, for drinking purposes in Baghdad City. Further, for carrying out the investigation, the data was collected from the Ministry of Water Resources of Baghdad, which represents water samples drawn from 114 wells in Al-Karkh and Al-Rusafa sides of Baghdad city. With the aim of further determining WQI, four water parameters such as (i) pH, (ii) Chloride (Cl), (iii) Sulfate (SO4), and (iv) Total dissolved solids (TDS), were taken into consideration. According to the computed WQI, the distribution of the groundwater samples, with respect to their quality classes such as excellent, good, poor, very poor and unfit for human drinking purpose, was found to be

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Publication Date
Tue Mar 20 2018
Journal Name
Offshore Technology Conference Asia
Prediction of Hydrate Phase Equilibrium Conditions for Different Gas Mixtures
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Abstract<p>Gas hydrate formation poses a significant threat to the production, processing, and transportation of natural gas. Accurate predictions of gas hydrate equilibrium conditions are essential for designing the gas production systems at safe operating conditions and mitigating the problems caused by hydrates formation. A new hydrate correlation for predicting gas hydrate equilibrium conditions was obtained for different gas mixtures containing methane, nitrogen and carbon dioxide. The new correlation is proposed for a pressure range of 1.7-330 MPa, a temperature range of 273-320 K, and for gas mixtures with specific gravity range of 0.553 to 1. The nonlinear regression technique was applie</p> ... Show More
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